writeHeinzNodes(BioNet)
writeHeinzNodes()所属R语言包：BioNet
Write node input file for HEINZ
亨氏写节点的输入文件
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Function to write an input file with the node scores for HEINZ. This file is used together with the edge input file to calculate the maximum scoring subnetwork of the graph. The scores are matched by their names to the nodes of the network, therefore if nodes.scores are provided as a vector or matrix, the vector has to be named, respectively the matrix has to be provided with rownames. If the network contains more nodes than the score vector, the nodes without a score are scored with the average over all nodes. If the nodes should not be scored and used for the calculation of the maximum scoring subnetwork, draw a subnetwork subNetwork first and use this for the argument network.
函数写亨氏节点分数的输入文件。这个文件是用来边输入文件来计算的最高得分子网图。分数是由他们的名字相匹配的网络节点，向量或矩阵，如果nodes.scores的规定，因此向量已被命名，分别被与rownames提供的矩阵。如果网络中包含多个节点比得分向量，没有得分的节点的所有节点的平均得分。如果节点不应该被拿下，并用于计算的最高得分子网，画出一个子网subNetwork第一次使用的网络参数。
用法----------Usage----------
writeHeinzNodes(network, file, node.scores=0, use.score=FALSE)
参数----------Arguments----------
参数：network
Network from which to calculate the maximum scoring subnetwork.
从计算的最高得分子网网络。
参数：file
File to write to.
文件写入。
参数：node.scores
Numeric vector or matrix of scores for the nodes of the network. Names of the vector or rownames of the matrix have to correspond to the PPI identifiers of the network. The scores can also be used from the node attribute "score", given one score for each node.
数字向量或矩阵网络节点的分数。向量或矩阵rownames名称有对应的PPI网络标识符。分数也可以用于从节点的属性“得分”一分给每个节点。
参数：use.score
Boolean value, whether to use the node attribute "score" in the network as node scores.
布尔值，是否使用节点属性“得分”在网络节点的分数。
Details
详情----------Details----------
Use scoreNodes or scoreFunctionto derive scores from a vector of p-values.
使用scoreNodes或scoreFunction来自p值向量的分数。
作者（S）----------Author(s)----------
Daniela Beisser
参见----------See Also----------
writeHeinzEdges and writeHeinz
writeHeinzEdges和writeHeinz
举例----------Examples----------
#create small network[建立小型网络]
library(DLBCL)
data(interactome)
small.net <- subNetwork(nodes(interactome)[0:15], interactome)
scores <- c(1:length(nodes(small.net)))
names(scores) <- nodes(small.net)
## Not run: writeHeinzNodes(network=small.net, file="test_nodes", node.scores=scores)[＃不运行：writeHeinzNodes（网络= small.net，文件=“test_nodes”，node.scores分数）]
# use Lymphoma data and graph to find module[使用淋巴瘤的数据和图找到模块]
library(DLBCL)
data(interactome)
data(dataLym)
# get induced subnetwork for all genes contained on the chip[在芯片上包含的所有基因诱导子网]
chipGraph <- subNetwork(dataLym$label, interactome)
## Not run: writeHeinzEdges(network=chipGraph, file="lymphoma_edges_001", use.score=FALSE)[＃无法运行：writeHeinzEdges（网络= chipGraph，文件=“lymphoma_edges_001”，use.score = FALSE）]
score <- dataLym$score001
names(score) <- dataLym$label
## Not run: writeHeinzNodes(network=chipGraph, file="lymphoma_nodes_001", node.scores=score)[＃无法运行：writeHeinzNodes（网络= chipGraph，文件=“lymphoma_nodes_001”，node.scores =得分）]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-2-25 13:40:41
